Testing the effect of deviance on similarity-based structure and certainty.
Hypothesis: We predict that as a new agent’s deviance from the group stereotype increases there will be a transition from group updating to subgroup formation to subtype formation. This will be reflected in participants’ similarity-rating derived dendrograms. Same as V3
Method changes:
only 25%/50%/75% deviancy
600 participants (increased from 300)
PNS scale added
Note: data for prediction values are corrected in R script due to coding error
| 0.25 (N=183) |
0.5 (N=184) |
0.75 (N=193) |
Overall (N=560) |
|
|---|---|---|---|---|
| age | ||||
| Mean (SD) | 35.5 (11.4) | 36.8 (13.2) | 36.2 (11.3) | 36.2 (12.0) |
| Median [Min, Max] | 33.0 [18.0, 79.0] | 33.0 [18.0, 93.0] | 34.0 [19.0, 75.0] | 34.0 [18.0, 93.0] |
| race | ||||
| American Indian or Alaska Native | 3 (1.6%) | 1 (0.5%) | 1 (0.5%) | 5 (0.9%) |
| Asian | 14 (7.7%) | 11 (6.0%) | 24 (12.4%) | 49 (8.8%) |
| Black or African-American | 9 (4.9%) | 13 (7.1%) | 13 (6.7%) | 35 (6.3%) |
| Hispanic/Latinx | 6 (3.3%) | 13 (7.1%) | 9 (4.7%) | 28 (5.0%) |
| Other | 2 (1.1%) | 1 (0.5%) | 2 (1.0%) | 5 (0.9%) |
| White | 149 (81.4%) | 145 (78.8%) | 144 (74.6%) | 438 (78.2%) |
| gender | ||||
| Man | 85 (46.4%) | 71 (38.6%) | 96 (49.7%) | 252 (45.0%) |
| Non-binary | 2 (1.1%) | 2 (1.1%) | 2 (1.0%) | 6 (1.1%) |
| Prefer not to answer | 2 (1.1%) | 1 (0.5%) | 5 (2.6%) | 8 (1.4%) |
| Woman | 94 (51.4%) | 110 (59.8%) | 90 (46.6%) | 294 (52.5%) |
| 0.25 (N=15) |
0.5 (N=15) |
0.75 (N=9) |
Overall (N=39) |
|
|---|---|---|---|---|
| age | ||||
| Mean (SD) | 35.3 (14.2) | 43.5 (17.6) | 37.8 (11.7) | 39.0 (15.2) |
| Median [Min, Max] | 28.0 [21.0, 62.0] | 39.0 [20.0, 81.0] | 34.0 [25.0, 57.0] | 34.0 [20.0, 81.0] |
| race | ||||
| Asian | 3 (20.0%) | 1 (6.7%) | 0 (0%) | 4 (10.3%) |
| Black or African-American | 2 (13.3%) | 2 (13.3%) | 5 (55.6%) | 9 (23.1%) |
| Hispanic/Latinx | 1 (6.7%) | 0 (0%) | 0 (0%) | 1 (2.6%) |
| White | 9 (60.0%) | 12 (80.0%) | 3 (33.3%) | 24 (61.5%) |
| Other | 0 (0%) | 0 (0%) | 1 (11.1%) | 1 (2.6%) |
| gender | ||||
| Man | 6 (40.0%) | 7 (46.7%) | 4 (44.4%) | 17 (43.6%) |
| Non-binary | 1 (6.7%) | 0 (0%) | 0 (0%) | 1 (2.6%) |
| Woman | 8 (53.3%) | 8 (53.3%) | 4 (44.4%) | 20 (51.3%) |
| Prefer not to answer | 0 (0%) | 0 (0%) | 1 (11.1%) | 1 (2.6%) |
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: corrresp
Chisq Df Pr(>Chisq)
opinion_round 280.1120 1 < 2.2e-16 ***
Deviant_threshold 10.3110 2 0.005768 **
opinion_round:Deviant_threshold 0.2399 2 0.886973
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 1 opinion_round.trend SE df asymp.LCL asymp.UCL z.ratio p.value
overall 0.0928 0.00555 Inf 0.0819 0.104 16.718 <.0001
Results are averaged over the levels of: Deviant_threshold
Confidence level used: 0.95 $emmeans
Deviant_threshold emmean SE df asymp.LCL asymp.UCL z.ratio p.value
0.25 1.104 0.0516 Inf 1.003 1.205 21.408 <.0001
0.5 0.992 0.0512 Inf 0.892 1.092 19.387 <.0001
0.75 0.897 0.0500 Inf 0.799 0.995 17.953 <.0001
Results are given on the logit (not the response) scale.
Confidence level used: 0.95
$contrasts
contrast estimate SE df asymp.LCL
Deviant_threshold0.25 - Deviant_threshold0.5 0.1119 0.0725 Inf -0.0581
Deviant_threshold0.25 - Deviant_threshold0.75 0.2067 0.0716 Inf 0.0388
Deviant_threshold0.5 - Deviant_threshold0.75 0.0948 0.0714 Inf -0.0725
asymp.UCL z.ratio p.value
0.282 1.543 0.2708
0.375 2.885 0.0109
0.262 1.329 0.3792
Results are given on the log odds ratio (not the response) scale.
Confidence level used: 0.95
Conf-level adjustment: tukey method for comparing a family of 3 estimates
P value adjustment: tukey method for comparing a family of 3 estimates Type III Analysis of Variance Table with Satterthwaite's method
Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
targetpair 100 100 1 560 0.4284 0.513
Deviant_threshold 46136 46136 1 560 196.8115 <2e-16 ***
targetpair:Deviant_threshold 26799 26799 1 560 114.3235 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1$emtrends
targetpair Deviant_threshold.trend SE df lower.CL upper.CL t.ratio p.value
DN -63.27 3.92 560 -71.0 -55.57 -16.141 <.0001
NN -8.44 3.29 560 -14.9 -1.97 -2.561 0.0107
Degrees-of-freedom method: satterthwaite
Confidence level used: 0.95
$contrasts
contrast estimate SE df lower.CL upper.CL t.ratio p.value
DN - NN -54.8 5.13 560 -64.9 -44.8 -10.692 <.0001
Degrees-of-freedom method: satterthwaite
Confidence level used: 0.95 Analysis of Variance Table
Response: k
Df Sum Sq Mean Sq F value Pr(>F)
Deviant_threshold 2 34.625 17.3123 33.145 2.51e-14 ***
Residuals 557 290.937 0.5223
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1$emmeans
Deviant_threshold emmean SE df lower.CL upper.CL t.ratio p.value
0.25 1.75 0.0534 557 1.65 1.86 32.823 <.0001
0.5 2.12 0.0533 557 2.02 2.23 39.866 <.0001
0.75 2.36 0.0520 557 2.25 2.46 45.301 <.0001
Confidence level used: 0.95
$contrasts
contrast estimate SE df lower.CL
Deviant_threshold0.25 - Deviant_threshold0.5 -0.370 0.0755 557 -0.548
Deviant_threshold0.25 - Deviant_threshold0.75 -0.603 0.0746 557 -0.778
Deviant_threshold0.5 - Deviant_threshold0.75 -0.233 0.0745 557 -0.408
upper.CL t.ratio p.value
-0.1932 -4.910 <.0001
-0.4279 -8.088 <.0001
-0.0576 -3.124 0.0053
Confidence level used: 0.95
Conf-level adjustment: tukey method for comparing a family of 3 estimates
P value adjustment: tukey method for comparing a family of 3 estimates Deviant_threshold emmean SE df null t.ratio p.value
0.25 1.75 0.0534 557 2 -4.613 <.0001
0.5 2.12 0.0533 557 2 2.328 0.9899
0.75 2.36 0.0520 557 2 6.856 1.0000
P values are left-tailed # A tibble: 2 × 13
model term estimate std.error statistic p.value conf.low
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 below_.5 Deviant_threshold -17.8 10.9 -1.63 0.103 -39.2
2 above_.5 Deviant_threshold 6.69 10.9 0.616 0.539 -14.7
conf.high r.squared adj.r.squared df df.residual nobs
<dbl> <dbl> <dbl> <dbl> <int> <int>
1 3.61 0.00727 0.00455 1 365 367
2 28.1 0.00101 -0.00165 1 375 377Analysis of Variance Table
Response: confidence
Df Sum Sq Mean Sq F value Pr(>F)
deviance 2 1858 929.19 1.3374 0.2634
Residuals 557 386994 694.78 $emmeans
deviance emmean SE df lower.CL upper.CL t.ratio p.value
0.25 53.6 1.95 557 49.8 57.4 27.501 <.0001
0.5 49.1 1.94 557 45.3 52.9 25.283 <.0001
0.75 50.8 1.90 557 47.1 54.5 26.776 <.0001
Confidence level used: 0.95
$contrasts
contrast estimate SE df lower.CL upper.CL t.ratio
deviance0.25 - deviance0.5 4.45 2.75 557 -2.01 10.92 1.619
deviance0.25 - deviance0.75 2.78 2.72 557 -3.61 9.17 1.023
deviance0.5 - deviance0.75 -1.67 2.72 557 -8.05 4.71 -0.616
p.value
0.2386
0.5628
0.8115
Confidence level used: 0.95
Conf-level adjustment: tukey method for comparing a family of 3 estimates
P value adjustment: tukey method for comparing a family of 3 estimates | 0.25 (N=183) |
0.5 (N=184) |
0.75 (N=193) |
Overall (N=560) |
|
|---|---|---|---|---|
| pred_maj | ||||
| Yes | 151 (82.5%) | 143 (77.7%) | 153 (79.3%) | 447 (79.8%) |
| No | 32 (17.5%) | 36 (19.6%) | 36 (18.7%) | 104 (18.6%) |
| Missing | 0 (0%) | 5 (2.7%) | 4 (2.1%) | 9 (1.6%) |
# A tibble: 4 × 14
# Groups: pred_maj [2]
pred_maj id term estimate std.error statistic p.value
<lgl> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 FALSE below_.5 Deviant_threshold -5.56 22.6 -0.246 0.807
2 FALSE above_.5 Deviant_threshold 27.1 21.2 1.28 0.206
3 TRUE below_.5 Deviant_threshold -17.6 12.1 -1.45 0.147
4 TRUE above_.5 Deviant_threshold 1.45 12.5 0.116 0.908
conf.low conf.high r.squared adj.r.squared df df.residual nobs
<dbl> <dbl> <dbl> <dbl> <dbl> <int> <int>
1 -50.7 39.6 0.000915 -0.0142 1 66 68
2 -15.3 69.5 0.0227 0.00877 1 70 72
3 -41.4 6.22 0.00719 0.00379 1 292 294
4 -23.1 26.0 0.0000456 -0.00336 1 294 296Analysis of Variance Table
Response: confidence
Df Sum Sq Mean Sq F value Pr(>F)
deviance 2 1651 825.4 1.2296 0.2932
pred_maj 1 13775 13774.9 20.5192 7.258e-06 ***
deviance:pred_maj 2 1303 651.3 0.9701 0.3797
Residuals 545 365868 671.3
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1| 0.25 (N=183) |
0.5 (N=184) |
0.75 (N=193) |
Overall (N=560) |
|
|---|---|---|---|---|
| pns_med | ||||
| High | 76 (41.5%) | 86 (46.7%) | 106 (54.9%) | 268 (47.9%) |
| Low | 107 (58.5%) | 98 (53.3%) | 87 (45.1%) | 292 (52.1%) |
# A tibble: 4 × 14
# Groups: pns_med [2]
pns_med id term estimate std.error statistic p.value
<chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 High below_.5 Deviant_threshold -17.7 16.4 -1.08 0.282
2 High above_.5 Deviant_threshold 15.1 15.0 1.00 0.317
3 Low below_.5 Deviant_threshold -18.9 14.7 -1.29 0.199
4 Low above_.5 Deviant_threshold -5.57 15.7 -0.354 0.724
conf.low conf.high r.squared adj.r.squared df df.residual nobs
<dbl> <dbl> <dbl> <dbl> <dbl> <int> <int>
1 -50.1 14.7 0.00724 0.00103 1 160 162
2 -14.6 44.7 0.00527 0.0000344 1 190 192
3 -47.8 10.0 0.00812 0.00324 1 203 205
4 -36.6 25.4 0.000686 -0.00478 1 183 185Analysis of Variance Table
Response: confidence
Df Sum Sq Mean Sq F value Pr(>F)
deviance 2 1858 929.19 1.3430 0.26190
pns_med 1 2823 2823.03 4.0804 0.04387 *
deviance:pns_med 2 882 440.84 0.6372 0.52916
Residuals 554 383289 691.86
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1| 0 (N=560) |
1 (N=560) |
2 (N=560) |
3 (N=560) |
4 (N=560) |
5 (N=560) |
6 (N=560) |
7 (N=560) |
8 (N=560) |
9 (N=560) |
10 (N=560) |
11 (N=560) |
Overall (N=6720) |
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| trialnum | |||||||||||||
| 0 | 98 (17.5%) | 91 (16.3%) | 86 (15.4%) | 96 (17.1%) | 92 (16.4%) | 89 (15.9%) | 91 (16.3%) | 97 (17.3%) | 98 (17.5%) | 101 (18.0%) | 99 (17.7%) | 83 (14.8%) | 1121 (16.7%) |
| 1 | 107 (19.1%) | 82 (14.6%) | 97 (17.3%) | 95 (17.0%) | 87 (15.5%) | 99 (17.7%) | 105 (18.8%) | 90 (16.1%) | 98 (17.5%) | 90 (16.1%) | 102 (18.2%) | 98 (17.5%) | 1150 (17.1%) |
| 2 | 99 (17.7%) | 93 (16.6%) | 98 (17.5%) | 88 (15.7%) | 88 (15.7%) | 110 (19.6%) | 86 (15.4%) | 97 (17.3%) | 102 (18.2%) | 79 (14.1%) | 100 (17.9%) | 113 (20.2%) | 1153 (17.2%) |
| 3 | 89 (15.9%) | 92 (16.4%) | 114 (20.4%) | 93 (16.6%) | 95 (17.0%) | 90 (16.1%) | 94 (16.8%) | 93 (16.6%) | 86 (15.4%) | 100 (17.9%) | 83 (14.8%) | 90 (16.1%) | 1119 (16.7%) |
| 4 | 84 (15.0%) | 113 (20.2%) | 88 (15.7%) | 98 (17.5%) | 96 (17.1%) | 80 (14.3%) | 95 (17.0%) | 82 (14.6%) | 91 (16.3%) | 87 (15.5%) | 78 (13.9%) | 78 (13.9%) | 1070 (15.9%) |
| 5 | 83 (14.8%) | 89 (15.9%) | 77 (13.8%) | 90 (16.1%) | 102 (18.2%) | 92 (16.4%) | 89 (15.9%) | 101 (18.0%) | 85 (15.2%) | 103 (18.4%) | 98 (17.5%) | 98 (17.5%) | 1107 (16.5%) |